Well that’s true if you have a live animal producing your meat. Not sure that applies if the meat is lab grown though?
Well that’s true if you have a live animal producing your meat. Not sure that applies if the meat is lab grown though?
100% they absolutely were.
Give geneticists 20 years, we’ll have lab grown T-Rex in the grocery store
Can you provide your docker-compose entry or your docker run command?
Okay, thanks for giving me that, I’ll investigate further tonight
So I just spot checked. Both shows work, you just have to not click an episode anymore.
E.g, https://pbskids.org/videos/design-squad -> design-squad
Thank you for telling me, I’ll update the readme
Hmmm. I just double checked and my episodes are still downloading. But maybe newer shows have a different format… What’s the exact error? I’ll try to reproduce and fix.
The streaming was easy, just declared I wasn’t paying for it anymore lol. We still have a crappy version of Spotify for free because of another service (ISP or phone plan something like that), but it’s purely used as a backup.
Jellyfin’s interface is a bit clunky as a music client in my experience. FinAmp looks cool but it’s still early on.
Navidrome does smart playlist, crossfading, gapless, flac streaming, and flac to opus transcoding. Those are sorta my core requirements, and Navidrome + the clients we use handles them all with aplomb.
And actually that’s another great feature I enjoy for Navidrome, there are dozens of excellent clients, so if one of them falls short for someone they can find one that they enjoy.
As for the user playlist thing… I haven’t seen anything like that but maybe I’m misunderstanding.
That’s fair!
Yeah Music Assistant uses Snapcast, which has been fun. I did try squeeze, but haven’t had a reason to switch so far
It’s a crappy python script I packaged in a docker container lol. Turns out PBS kids uses an open unauthenticated CDN for serving videos to the website and apps.
I can share if you want, but it’ll take me until tomorrow to make it public
Certainly!
Jellyfin I use for video content. I find its music functions lackluster.
Navidrome I use (and my family uses) for personal listening.
Music around the house, like on one or more of my casting capable speakers / tvs I use Music Assistant. Also let’s me do automations easily, and doesn’t tie up an android phones media’s output. Struggled with earbuds while casting taking over audio for too long before deploying Music Assistant!
I will add, what helped me the most with Plex/Jellyfin load was using Tdarr to normalize my library’s formats into something easy to direct stream to any device without transcoding.
It’s old but fairly beefy. Most of the RAM is reserved for ZFS reads, but in reality theres tons of headroom.
CPU: 2x E5-2630L v2
Motherboard: Intel S2600CP
RAM: 16x8GB DDR3 1333 ECC
Disk:
I’ll probably be moving this to a cluster of mini computers whenever prices look right, just for power efficiency.
Minus the storage the box cost me about $600, mostly in RAM. The CPUs were like $20 each, the mobo was about $150, etc
The general list:
With all the supporting services:
Server:
Containers: 76
Running: 74
Paused: 0
Stopped: 2
Images: 92
Not trying to be rude, but that’s a question of how the engine uses the CPU vs GPU implementation, not a measure of apples to apples.
Comparing modern games with CPU particle physics to the heyday of GPU Physx there is no comparison. CPU physics (and Physx) are more accurate, less buggy, and generally not impactful in performance.
I mean, does it work worse? UE4/Havok and Unigine all use CPU Physx. And every other engine I know of uses a custom particle physics implementation and seem far better at it than GPU Physx ever was.
On GPU I remember physx being super buggy since the GPU calculations were very low precision, and that was if you had an Nvidia card. It made AMD cards borderline unplayable in many games that were doing extensive particle physics for no other reason than to punish AMD in benchmarks.
2ghz does not measure it’s computing power though, only the cycle speed. Two very different things.
An objective measure is a simple benchmark:
Here’s a quad core 1.5ghz RISC-V SoC (noted as VisionFive 2) vs a quad core 1.8ghz ARM chip (noted as Raspberry Pi 400).
It’s not even remotely close to usable for all but the most basic of tasks https://www.phoronix.com/review/visionfive2-riscv-benchmarks/6